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Safety-margin-based design and redesign considering mixed epistemic model uncertainty and aleatory parameter uncertainty

Abstract : At the initial design stage engineers often rely on low-fidelity models that have high epistemic uncertainty. Traditional safety-margin-based deterministic design resorts to testing (e.g. prototype experiment, evaluation of high-fidelity simulation, etc.) to reduce epistemic uncertainty and achieve targeted levels of safety. Testing is used to calibrate models and prescribe redesign when tests are not passed. After calibration, reduced epistemic model uncertainty can be leveraged through redesign to restore safety or improve design performance; however, redesign may be associated with substantial costs or delays. In this paper, a methodology is described for optimizing the safety-margin-based design, testing, and redesign process to allow the designer to tradeoff between the risk of future redesign and the possible performance and reliability benefits. The proposed methodology represents the epistemic model uncertainty with a Kriging surrogate and is applicable in a wide range of design problems. The method is illustrated on a cantilever beam bending example and then a sounding rocket example. It is shown that redesign acts as a type of quality control measure to prevent an undesirable initial design from being accepted as the final design. It is found that the optimal design/redesign strategy for maximizing expected design performance includes not only redesign to correct an initial design that is later revealed to be unsafe, but also redesign to improve performance when an initial design is later revealed to be too conservative (e.g. too heavy).
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Preprints, Working Papers, ...
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Contributor : Florent Breuil <>
Submitted on : Wednesday, July 3, 2019 - 11:34:57 AM
Last modification on : Friday, June 26, 2020 - 2:30:07 PM

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  • HAL Id : hal-02171882, version 1
  • ARXIV : 1904.08978


Nathaniel B. Price, Mathieu Balesdent, Sebastien Defoort, Rodolphe Le Riche, Nam H. Kim, et al.. Safety-margin-based design and redesign considering mixed epistemic model uncertainty and aleatory parameter uncertainty. 2019. ⟨hal-02171882⟩



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